7 papers
Efficient training of photonic quantum generative models
Felix Gottlieb, Chayma Faraji, Rawad Mezher +3
The topic of generative learning has gained traction within the field of quantum machine learning, in particular with the advent of train-on-classical, deploy-on-quantum methods. T…
Quantum Energetic Advantage before Computational Advantage in Boson Sampling
Ariane Soret, Nessim Dridi, Stephen C. Wein +3
Understanding the energetic efficiency of quantum computers is essential for assessing their scalability and for determining whether quantum technologies can outperform classical c…
Enhanced Fault-tolerance in Photonic Quantum Computing: Comparing the Honeycomb Floquet Code and the Surface Code in Tailored Architecture
Théo Dessertaine, Boris Bourdoncle, Aurélie Denys +5
Fault-tolerant quantum computing is crucial for realizing large-scale quantum computation, and the interplay between hardware architecture and quantum error-correcting codes is a k…
Minimizing resource overhead in fusion-based quantum computation using hybrid spin-photon devices
Stephen C. Wein, Timothée Goubault de Brugière, Luka Music +3
We present three schemes for constructing a (2,2)-Shor-encoded 6-ring photonic resource state for fusion-based quantum computing, each relying on a different type of photon source.…
Towards practical secure delegated quantum computing with semi-classical light
Boris Bourdoncle, Pierre-Emmanuel Emeriau, Paul Hilaire +3
Secure Delegated Quantum Computation (SDQC) protocols are a vital piece of the future quantum information processing global architecture since they allow end-users to perform their…
A Photonic Parameter-shift Rule: Enabling Gradient Computation for Photonic Quantum Computers
Axel Pappalardo, Pierre-Emmanuel Emeriau, Giovanni de Felice +5
We present a method for gradient computation in quantum algorithms implemented on linear optical quantum computing platforms. While parameter-shift rules have become a staple in qu…